Optimization of Extrusion Process Parameters for Medical TPU Thin-walled Microtubes
To solve the problems of the process parameters of thermoplastic polyurethane elastomer(TPU)thin-walled microtube extrusion,the extrusion processes of thin-walled TPU microtubes with a diameter of less than 2 mm were studied by the numerical simulation method,and the process parameters of specific sizes were optimized by combining RBF neural network and NSGA-Ⅱ multi-objective optimization algorithm.Firstly,the initial three-dimensional model of the orifice flow channel was established,and the flow channels were optimized according to the characteristics of thin-walled microtube extrusion combined with the numerical model methods.On this basis,the influences of extrusion process parameters on the extrusion molding were studied.The results show that melt temperature has little effect on pipe size.The extrusion flow rate,traction speed and gas injection pressure are more suitable for the pipe size control.Then,the optimal Latin hypercube experimental design method was used to select the sample points,and the extrusion process agent model based on RBF neural network was established.Through comparison,the results show that the RBF neural network model has high accuracy,and the optimal process parameters of specific sizes are obtained by combining NSGA-Ⅱ algorithm.The above optimization methods for TPU thin-walled microtubes could obtain qualified products,showing guiding significances for the actual extrusion processes.
万方数据
维普
